Systems Biomedicine of Rabies Delineates the Affected Signaling Pathways

Tracking lethal threat: in-depth review of rabies

An infectious disease known as rabies (family Rhabdoviridae, genus Lyssavirus) causes severe damage to mammals' central nervous systems (CNS). This illness has been around for a very long time. The majority of human cases of rabies take place in underdeveloped regions of Africa and Asia. Following viral transmission, the Rhabdovirus enters the peripheral nervous system and proceeds to the CNS, where it targets the encephalon and produces encephalomyelitis. Postbite prophylaxis requires laboratory confirmation of rabies in both people and animals. All warm-blooded animals can transmit the Lyssavirus infection, while the virus can also develop in the cells of cold-blooded animals. In the 21st century, more than 3 billion people are in danger of contracting the rabies virus in more than 100 different nations, resulting in an annual death toll of 50,000-59,000. There are three important elements in handling rabies disease in post exposure prophylaxis (PEP), namely wound care, administration of anti-rabies serum, and anti-rabies vaccine. Social costs include death, lost productivity as a result of early death, illness as a result of vaccination side effects, and the psychological toll that exposure to these deadly diseases has on people. Humans are most frequently exposed to canine rabies, especially youngsters and the poor, and there are few resources available to treat or prevent exposure, making prevention of human rabies challenging.

STARGATE-X: a Python package for statistical analysis on the REACTOME network

Many important aspects of biological knowledge at the molecular level can be represented by pathways. Through their analysis, we gain mechanistic insights and interpret lists of interesting genes from experiments (usually omics and functional genomic experiments). As a result, pathways play a central role in the development of bioinformatics methods and tools for computing predictions from known molecular-level mechanisms. Qualitative as well as quantitative knowledge about pathways can be effectively represented through biochemical networks linking the biochemical reactions and the compounds (e.g., proteins) occurring in the considered pathways. So, repositories providing biochemical networks for known pathways play a central role in bioinformatics and in systems biology. Here we focus on Reactome, a free, comprehensive, and widely used repository for biochemical networks and pathways. In this paper, we: (1) introduce a tool StARGate-X (STatistical Analysis of the Reactome multi-GrAph Through nEtworkX) to carry out an automated analysis of the connectivity properties of Reactome biochemical reaction network and of its biological hierarchy (i.e., cell compartments, namely, the closed parts within the cytosol, usually surrounded by a membrane); the code is freely available at https://github.com/marinoandrea/stargate-x; (2) show the effectiveness of our tool by providing an analysis of the Reactome network, in terms of centrality measures, with respect to in- and out-degree. As an example of usage of StARGate-X, we provide a detailed automated analysis of the Reactome network, in terms of centrality measures. We focus both on the subgraphs induced by single compartments and on the graph whose nodes are the strongly connected components. To the best of our knowledge, this is the first freely available tool that enables automatic analysis of the large biochemical network within Reactome through easy-to-use APIs (Application Programming Interfaces).

The mirror like expression of genes involved in the FOXO signaling pathway could be effective in the pathogenesis of human lymphotropic virus type 1 (HTLV-1) through disruption of the downstream pathways

OBJECTIVES

Human lymphotropic virus type 1 (HTLV-1) is the cause of two major diseases, ATLL and HAM/TSP in a percentage of carriers. Despite progress in understanding the pathogenesis of these two diseases, the exact pathogenesis mechanism is still not well understood. High-throughput technologies have revolutionized medical research. This study aims to investigate the mechanism of pathogenesis of these two diseases using the results of high-throughput analysis of microarray datasets.

RESULTS

A total of 100 differentially expressed genes were found between ATLL and HAM/TSP. After constructing protein-protein network and further analyzing, proteins including ATM, CD8, CXCR4, PIK3R1 and CD2 were found as the hub ones between ATLL and HAM/TSP. Finding the modules of the subnetwork revealed the enrichment of two common pathways including FOXO signaling pathway and Cell cycle with two common genes including ATM and CDKN2D. Unlike ATLL, ATM gene had higher expressions in HAM/TSP patients. The expression of CDKN2D was increased in ATLL patients. The results of this study could be helpful for understanding the pathogenic mechanism of these two diseases in the same signaling pathways.

Early Transcriptional Changes in Rabies Virus-Infected Neurons and Their Impact on Neuronal Functions

Rabies is a zoonotic disease caused by rabies virus (RABV). As rabies advances, patients develop a variety of severe neurological symptoms that inevitably lead to coma and death. Unlike other neurotropic viruses that can induce symptoms of a similar range, RABV-infected post-mortem brains do not show significant signs of inflammation nor the structural damages on neurons. This suggests that the observed neurological symptoms possibly originate from dysfunctions of neurons. However, many aspects of neuronal dysfunctions in the context of RABV infection are only partially understood, and therefore require further investigation. In this study, we used differentiated neurons to characterize the RABV-induced transcriptomic changes at the early time-points of infection. We found that the genes modulated in response to the infection are particularly involved in cell cycle, gene expression, immune response, and neuronal function-associated processes. Comparing a wild-type RABV to a mutant virus harboring altered matrix proteins, we found that the RABV matrix protein plays an important role in the early down-regulation of host genes, of which a significant number is involved in neuronal functions. The kinetics of differentially expressed genes (DEGs) are also different between the wild type and mutant virus datasets. The number of modulated genes remained constant upon wild-type RABV infection up to 24 h post-infection, but dramatically increased in the mutant condition. This result suggests that the intact viral matrix protein is important to control the size of host gene modulation. We then examined the signaling pathways previously studied in relation to the innate immune responses against RABV, and found that these pathways contribute to the changes in neuronal function-associated processes. We further examined a set of regulated genes that could impact neuronal functions collectively, and demonstrated in calcium imaging that indeed the spontaneous activity of neurons is influenced by RABV infection. Overall, our findings suggest that neuronal function-associated genes are modulated by RABV early on, potentially through the viral matrix protein-interacting signaling molecules and their downstream pathways.

Transcriptome Profile During Rabies Virus Infection: Identification of Human CXCL16 as a Potential New Viral Target

Rabies virus (RABV), the causative agent for rabies disease is still presenting a major public health concern causing approximately 60,000 deaths annually. This neurotropic virus (genus Lyssavirus, family Rhabdoviridae) induces an acute and almost always fatal form of encephalomyelitis in humans. Despite the lethal consequences associated with clinical symptoms of rabies, RABV limits neuro-inflammation without causing major histopathological lesions in humans. Nevertheless, information about the mechanisms of infection and cellular response in the central nervous system (CNS) remain scarce. Here, we investigated the expression of inflammatory genes involved in immune response to RABV (dog-adapted strain Tha) in mice, the most common animal model used to study rabies. To better elucidate the pathophysiological mechanisms during natural RABV infection, we compared the inflammatory transcriptome profile observed at the late stage of infection in the mouse brain (cortex and brain stem/cerebellum) with the ortholog gene expression in post-mortem brain biopsies of rabid patients. Our data indicate that the inflammatory response associated with rabies is more pronounced in the murine brain compared to the human brain. In contrast to murine transcription profiles, we identified CXC motif chemokine ligand 16 (CXCL16) as the only significant differentially expressed gene in post-mortem brains of rabid patients. This result was confirmed in vitro, in which Tha suppressed interferon alpha (IFN-α)-induced CXCL16 expression in human CNS cell lines but induced CXCL16 expression in IFN-α-stimulated murine astrocytes. We hypothesize that RABV-induced modulation of the CXCL16 pathway in the brain possibly affects neurotransmission, natural killer (NK) and T cell recruitment and activation. Overall, we show species-specific differences in the inflammatory response of the brain, highlighted the importance of understanding the potential limitations of extrapolating data from animal models to humans.

Rabies Infection: An Overview of Lyssavirus-Host Protein Interactions

Viruses are obligatory intracellular parasites that use cell proteins to take the control of the cell functions in order to accomplish their life cycle. Studying the viral-host interactions would increase our knowledge of the viral biology and mechanisms of pathogenesis. Studies on pathogenesis mechanisms of lyssaviruses, which are the causative agents of rabies, have revealed some important host protein partners for viral proteins, especially for most studied species, i.e. RABV. In this review article, the key physical lyssavirus-host protein interactions, their contributions to rabies infection, and their exploitation are discussed to improve the knowledge about rabies pathogenesis.

Systems Biomedicine of Primary and Metastatic Colorectal Cancer Reveals Potential Therapeutic Targets

Colorectal cancer (CRC) is one of the major causes of cancer deaths across the world. Patients' survival at time of diagnosis depends mainly on stage of the tumor. Therefore, understanding the molecular mechanisms from low-grade to high-grade stages of cancer that lead to cellular migration from one tissue/organ to another tissue/organ is essential for implementing therapeutic approaches. To this end, we performed a unique meta-analysis flowchart by identifying differentially expressed genes (DEGs) between normal, primary (primary sites), and metastatic samples (Colorectal metastatic lesions in liver and lung) in some Test datasets. DEGs were employed to construct a protein-protein interaction (PPI) network. A smaller network containing 39 DEGs was then extracted from the PPI network whose nodes expression induction or suppression alone or in combination with each other would inhibit tumor progression or metastasis. These DEGs were then verified by gene expression profiling, survival analysis, and multiple Validation datasets. We suggested for the first time that downregulation of mitochondrial genes, including ETHE1, SQOR, TST, and GPX3, would help colorectal cancer cells to produce more energy under hypoxic conditions through mechanisms that are different from "Warburg Effect". Augmentation of given antioxidants and repression of P4HA1 and COL1A2 genes could be a choice of CRC treatment. Moreover, promoting active GSK-3β together with expression control of EIF2B would prevent EMT. We also proposed that OAS1 expression enhancement can induce the anti-cancer effects of interferon-gamma, while suppression of CTSH hinders formation of focal adhesions. ATF5 expression suppression sensitizes cancer cells to anchorage-dependent death signals, while LGALS4 induction recovers cell-cell junctions. These inhibitions and inductions would be another combinatory mechanism that inhibits EMT and cell migration. Furthermore, expression inhibition of TMPO, TOP2A, RFC3, GINS1, and CKS2 genes could prevent tumor growth. Besides, TRIB3 suppression would be a promising target for anti-angiogenic therapy. SORD is a poorly studied enzyme in cancer, found to be upregulated in CRC. Finally, TMEM131 and DARS genes were identified in this study whose roles have never been interrogated in any kind of cancer, neither as a biomarker nor curative target. All the mentioned mechanisms must be further validated by experimental wet-lab techniques.

HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) versus adult T-cell leukemia/lymphoma (ATLL)

Objectives

Human T cell leukemia virus-1 (HTLV-1) infection may lead to one or both diseases including HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) or adult T cell leukemia lymphoma (ATLL). The complete interactions of the virus with host cells in both diseases is yet to be determined. This study aims to construct an interaction network for distinct signaling pathways in these diseases based on finding differentially expressed genes (DEGs) between HAM/TSP and ATLL.

Results

We identified 57 hub genes with higher criteria scores in the primary protein–protein interaction network (PPIN). The ontology-based enrichment analysis revealed following important terms: positive regulation of transcription from RNA polymerase II promoter, positive regulation of transcription from RNA polymerase II promoter involved in meiotic cell cycle and positive regulation of transcription from RNA polymerase II promoter by histone modification. The upregulated genes TNF, PIK3R1, HGF, NFKBIA, CTNNB1, ESR1, SMAD2, PPARG and downregulated genes VEGFA, TLR2, STAT3, TLR4, TP53, CHUK, SERPINE1, CREB1 and BRCA1 were commonly observed in all the three enriched terms in HAM/TSP vs. ATLL. The constructed interaction network was then visualized inside a mirrored map of signaling pathways for ATLL and HAM/TSP, so that the functions of hub genes were specified in both diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05521-y.

Lentiviral Expression of Rabies Virus Glycoprotein in the Rat Hippocampus Strengthens Synaptic Plasticity

Rabies virus (RABV) is a neurotropic virus exclusively infecting neurons in the central nervous system. RABV encodes five proteins. Among them, the viral glycoprotein (RVG) plays a key role in viral entry into neurons and rabies pathogenesis. It was shown that the nature of the C-terminus of the RABV G protein, which possesses a PDZ-binding motif (PBM), modulates the virulence of the RABV strain. The neuronal protein partners recruited by this PBM may alter host cell function. This study was conducted to investigate the effect of RVG on synaptic function in the hippocampal dentate gyrus (DG) of rat. Two μl (10⁸ T.U./ml) of the lentiviral vector containing RVG gene was injected into the DG of rat hippocampus. After 2 weeks, the rat's brain was cross-sectioned and RVG-expressing cells were detected by fluorescent microscopy. Hippocampal synaptic activity of the infected rats was then examined by recording the local field potentials from DG after stimulation of the perforant pathway. Short-term synaptic plasticity was also assessed by double pulse stimulation. Expression of RVG in DG increased long-term potentiation population spikes (LTP-PS), whereas no facilitation of LTP-PS was found in neurons expressing δRVG (deleted PBM). Furthermore, RVG and δRVG strengthened paired-pulse facilitation. Heterosynaptic long-term depression (LTD) in the DG was significantly blocked in RVG-expressing group compared to the control group. This blockade was dependent to PBM motif as rats expressing δRVG in the DG-expressed LTD comparable to the RVG group. Our data demonstrate that RVG expression facilitates both short- and long-term synaptic plasticity in the DG indicating that it may involve both pre- and postsynaptic mechanisms to alter synaptic function. Further studies are needed to elucidate the underlying mechanisms.

Unsupervised Learning and Multipartite Network Models: A Promising Approach for Understanding Traditional Medicine

The ultimate goal of precision medicine is to determine right treatment for right patients based on precise diagnosis. To achieve this goal, correct stratification of patients using molecular features and clinical phenotypes is crucial. During the long history of medical science, our understanding on disease classification has been improved greatly by chemistry and molecular biology. Nowadays, we gain access to large scale patient-derived data by high-throughput technologies, generating a greater need for data science including unsupervised learning and network modeling. Unsupervised learning methods such as clustering could be a better solution to stratify patients when there is a lack of predefined classifiers. In network modularity analysis, clustering methods can be also applied to elucidate the complex structure of biological and disease networks at the systems level. In this review, we went over the main points of clustering analysis and network modeling, particularly in the context of Traditional Chinese medicine (TCM). We showed that this approach can provide novel insights on the rationale of classification for TCM herbs. In a case study, using a modularity analysis of multipartite networks, we illustrated that the TCM classifications are associated with the chemical properties of the herb ingredients. We concluded that multipartite network modeling may become a suitable data integration tool for understanding the mechanisms of actions of traditional medicine.

Molecular Network Analysis in Rabies Pathogenesis Using Cooperative Game Theory

Background and Purpose

Recently, many researchers from different fields of science have been used networks to analyze complex relational big data. The identification of which nodes are more important than the others, known as centrality analysis, is a key issue in biological network analysis. Although, several centralities have been introduced degree, closeness, and betweenness centralities are the most popular. These centralities are based on the individual position of each node and the cooperation and synergies between nodes have been ignored.

Objectives

Since in many cases, the network function is a consequence of cooperation and interaction between nodes, classical centralities were extended to a group of nodes instead of only individual nodes using cooperative game theory concepts. In this study, we analyze the protein interaction network inferred in rabies disease and rank gene products based on group centrality measurements to identify the novel gene candidates.

Materials and Methods

For this purpose, we used a game-theoretic approach at three scenarios, where the power of a coalition of genes assessed using different criteria including the neighbors of genes in the network, and predefined importance of the genes in its neighborhood. The Shapley value of such a game was considered as a new centrality. In this study, we analyze the network of gene products implicates rabies. The network has 1059 nodes and 8844 edges and centrality analysis was performed using CINNA package in R software.

Results

Based on three scenarios, we selected genes among the highest Shapley value that had low ranking from classical centralities. The enrichment analysis among the selected genes in scenario 1 indicates important pathways in rabies pathogenesis. Pair-wise correlation analysis reveals that changing the weights of nodes at different scenarios can significantly affect the results of ranking genes in the network.

Conclusion

A prior knowledge about the disease and the topology of the network, enable us to design an appropriate game and consequently infer some biological important nodes (genes) in the network. Obviously, a single centrality cannot capture all significant features embedded in the network.

Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

UNaProd: A Universal Natural Product Database for Materia Medica of Iranian Traditional Medicine

BACKGROUND

Iranian traditional medicine (ITM) is a holistic medical system that uses a wide range of medicinal substances to treat disease. Reorganization and standardization of the data on ITM concepts is a necessity for optimal use of this rich source. In an initial step towards this goal, we created a database of ITM materia medica. Main Body. Primarily based on Makhzan al-Advieh, which is the most recent encyclopedia of materia medica in ITM with the largest number of monographs, a database of natural medicinal substances was created using both text mining methods and manual editing. UNaProd, a Universal Natural Product database for materia medica of ITM, is currently host to 2696 monographs, from herbal to animal to mineral compounds in 16 diverse attributes such as origin and scientific name. Currently, systems biology, and more precisely systems medicine and pharmacology, can be an aid in providing rationalizations for many traditional medicines and elucidating a great deal of knowledge they can offer to guide future research in medicine.

CONCLUSIONS

A database of materia medica is a stepping stone in creating a systems pharmacology platform of ITM that encompasses the relationships between the drugs, their targets, and diseases. UNaProd is hyperlinked to IrGO and CMAUP databases for Mizaj and molecular features, respectively, and it is freely available at http://jafarilab.com/unaprod/.

Natural Infection with Rabies Virus: A Histopathological and Immunohistochemical Study of Human Brains

Objectives

Despite all the efforts and increased knowledge of rabies, the exact mechanisms of infection and mortality from the rabies virus are not well understood. To understand the mechanisms underlying the pathogenicity of rabies virus infection, it is crucial to study the tissue that the rabies virus naturally infects in humans.

Methods

Cerebellum brain tissue from 9 human post mortem cases from Iran, who had been infected with rabies virus, were examined histopathologically and immunohistochemically to evaluate the innate immune responses against the rabies virus.

Results

Histopathological examination revealed inflammation of the infected cerebellum and immunohistochemical analyses showed an increased immunoreactivity of heat shock protein 70, interleukin-6, interleukin-1, tumor necrosis factor-alpha, caspase-3, caspase-9, toll-like receptor3 and toll-like receptor4 in the infected brain tissue.

Conclusion

These results indicated the involvement of innate immunity in rabies infected human brain tissue, which may aggravate the progression of this deadly disease.

A systematic survey of centrality measures for protein-protein interaction networks

Background

Numerous centrality measures have been introduced to identify “central” nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures.

Results

We used yeast PPINs to compare 27 common of centrality measures. The measures characterize and assort influential nodes of the networks. We applied principal component analysis (PCA) and hierarchical clustering and found that the most informative measures depend on the network’s topology. Interestingly, some measures had a high level of contribution in comparison to others in all PPINs, namely Latora closeness, Decay, Lin, Freeman closeness, Diffusion, Residual closeness and Average distance centralities.

Conclusions

The choice of a suitable set of centrality measures is crucial for inferring important functional properties of a network. We concluded that undertaking data reduction using unsupervised machine learning methods helps to choose appropriate variables (centrality measures). Hence, we proposed identifying the contribution proportions of the centrality measures with PCA as a prerequisite step of network analysis before inferring functional consequences, e.g., essentiality of a node.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0598-2) contains supplementary material, which is available to authorized users.